Neuroscience and Epistemology at ETech

At ETech, I had a fascinating conversation with Marie Bjerede, VP and General Manager of Qualcomm’s Portland Design Center. She was telling me how the threads we’d brought together at ETech had validated her own thinking and helped her bring together her private passions and her professional life. I asked her to write up our conversation, and she agreed. Here’s what Marie wrote (links are mine):

For years, I’ve been secretly (almost shamefully) allowing my hobby to seep into my work. I’m a high-tech executive for a living. I get paid to be rational, logical, objective, and analytical. And I get paid to produce results. But, being blessed with a team with the relentless habit of constantly producing results, I’ve had the luxury of tinkering. Not the metrics-driven six-sigma efficiency-oriented tinkering that a hard-headed technical leader can point to with pride. No, my tinkering is based in my hobby: epistemology (the branch of philosophy that asks the question, “What is knowledge?” “How do we know?”)

Over the past decade, an increasing number of popular books have been published that address classic questions in epistemology by drawing on recent research in neuroscience and results based on brain imaging. From Daniel Goleman’s work in emotional and social intelligence leading to his writings on research with the Dalai Lama and the Mind and Life Institute, to Gerald Edelman’s mind-blowing denunciation of mind-body duality via neural darwinism, to Antonio Damasio’s explication of the physical origins and building blocks of feeling and emotion, a picture has begun to emerge. A picture of minds that are entailed by their biology: brains that can act either as massively parallel processors that identify patterns and signal the pattern-matching results with emotions or as serial processors where any given set of inputs will lead, through inductive and deductive reasoning, to logical conclusions. Intuition and gut feelings come from one kind of thought, reason from another. Together, they balance each other and fill in each other’s blind spots.

So how does the balance of intuitive and logical thinkers affect a team’s results? Does it affect the balance between creativity and efficiency? What about individual and collective emotional and social intelligence? Are there brain states that enhance or degrade effectiveness, and if so, can they be learned (or unlearned)? How do beings with 4 billion of years of evolutionary selection for multi-modal communication fare in a digital, pure-verbal environment? How do physical spaces affect team results? These are the kinds of questions that have driven my compulsive tinkering. I’ve taken to referring to it as “applied epistemology” and considering myself a lay practitioner. One whose predilections, of necessity, are not discussed in tough-minded company.

Then, this Tuesday I was blown away. First, I got to see Elizabeth Churchill’s surprising and insightful presentation on socially oriented experience. Not only did she use Damasio’s work to lay a foundation for her explanations, she began with Descartes and worked her way there! Shortly thereafter I was fortunate enough to see Nicole Lazzaro’s very thoughtful treatment of the emotions and mental states that drive satisfying gaming experiences – again, including Damasio in the foundation as well as a shout-out to Paul Ekman’s work on universal emotions. That evening, I had the opportunity to hear first hand from John McCarthy himself how philosophy was foundational to his work in Artificial Intelligence, a theme which he elaborated on in his challenging Wednesday morning keynote (liberally referencing John Searle’s speech act theory.) Finally, there was Kathy Sierra’s delightfully provocative treatise on what neuroscience has to tell us about expertise, focus, and practice. Such a diverse set of insights that, to me, all look like varied applications of modern epistemology!!

So. Much gratitude for the useful brain states this emergent pattern has evoked. Epistemology is coming out of the closet for me!

Marie’s comments were music to my ears. A lot of what we try to do at ETech (as well as at other conferences and gatherings) is to bring together people who are connected in ways that are not obvious. We see an idea bubbling up, and try to build a program that helps other people to see the same trends that we do.

In the case of the connections between neuroscience, epistemology and computers, we’ve been noodling on this for a while. The success of Mind Hacks in 2004 showed us just how much people are fascinated with neuroscience; Kathy Sierra’s Creating Passionate Users helped us to see how it impacts product design and professional learning; we started seeing how game designers are the new rock stars of the computer industry, because they understand the role of emotion in application design.

Even further out, through our foo camp process (which could be summarized as “interesting people will lead you to interesting topics”), we found ourselves surprised by the number of people who are interested in “hacking their own brains.” (See Ed Boyden and Ramez Naam for two examples.) But this idea is hitting the mainstream. Timo Hannay pointed us to a recent poll in Nature about the legitimacy of using drugs to boost brain power.

But hey, if you read Steve Levy’s profile of me in Wired a few years ago, or John Markoff’s What the Dormouse Said, you’d realize that these connections between the science of mind and computer science are deeply rooted. As we pursue the idea of collective intelligence (which as I’ve often noted is the very heart of Web 2.0), we also go deeper into the question of just what intelligence is. We’re all closet epistemologists at O’Reilly… :-)

(I can’t resist a plug for Steve Talbott‘s two books, The Future Does Not Compute, which I published in 1995, and Devices of the Soul, which I published last year. Steve asks what parts of our humanity we are leaving out in our pursuit of technology — are we creating machines like us, or are we making ourselves more like them? Unlike Steve, I believe in the possibilities of machine intelligence, and but he provides an insightful and necessary challenge to assumptions about the benefits of technology.)

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